// Given the data structure below, write a solution that will aggregate the values both by
// which quarter of the year they occurred in and their forward sortation area (FSA), which is the first half of the canadian postal code.
const data = [
["M5V 3L9", 120.50, "2025-02-10", "Canada"],
["V6B 2W1", 250.00, "2025-01-12", "Canada"],
["M4C 1A1", 75.25, "2025-03-11", "Canada"],
["V6B 3H6", 400.00, "2025-04-10", "Canada"],
["K1A 0B1", 60.00, "2025-05-09", "Canada"],
["K1A 0B3", 34.00, "2025-06-08", "Canada"],
["V6B 0D2", 80.00, "2025-01-08", "Canada"],
]
// example output:
// {
// 'Q1': {
// 'M5V': 120.5,
// 'V6B': 330.0,
// 'M4C': 75.25
// },
// 'Q2': {
// 'V6B': 400.0,
// 'K1A': 94.0
// },
// }
The second revision, add this to the array: [“V6B 0D2", 80.00, "2025-10-08", "Canada"]
Their revision, add this to the array: ["V6B10D2", 80.00, "2025-01-08", "Pytown"],